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EXAMINING THE RELATIONSHIP BETWEEN GDP AND NATIONAL INCOME MODEL COMPONENTS OF 185 COUNTRIES IN 2013

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Assumption of National Income Model:  2 sector model help to explain the national income model and the changes  Increase  &  Decrease  in component C, I, G, X,M will change the national income (GDP). Similarly, changes in GDP will cause a change in national income (GDP).

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Coefficient Standard Error  t-ratio constant   4.71e+08 1.49e+09   0.32  Government -.1634183    .0336677  -4.85 Investment  1.256981 .011899 105.64 Consumption .9803206 .0097932 100.10 Import -1.150317 .0505533 -22.75 Export 1.134428 .0431802 26.27

n=185 R-squared= 1.000 F-statistic=99999.0 Prob> F = 0.0000

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A $1 increase in  government spending  leads to a  $0.16 decrease  in GDP (constant USD2010) A $1 increase in  Investment  leads to a  $1. 26 increase  in GDP (constant USD2010) A $1 increase in  Consumption  leads to a  $0.98 increase  in GDP (constant USD2010) A $1 increase in  Import  leads to a  $1.15 decrease  in GDP (constant USD2010) A $1 increase in  Export  leads to a  $1.13 increase  in GDP (constant USD2010)

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_cons = P>t = 0.753 The P>f result shows the regression is 0.000 which is significant. However, looking at the _cons, the p>t is greater than 0.05 which is insignificant. Therefore, there is an error in the regression.

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RSS Sample 1 (Lower Bracket) N= 70 countries        d.o.f= 70-6= 64    By regressing the GDP into GOV CONS INV IM EX RSS=  1.91E+19

Heteroskedastic Test (Goldfeld Quandt Test/GQ Test)

RSS Sample 2 (Upper Bracket) N= 70 countries        d.o.f= 70-6= 64     By regressing the GDP into GOV CONS INV IM EX RSS=  6.53E+22

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RSS= 1.91E+19                                        RSS= 6.53E+22 (lower bracket)                                       (upper bracket) ‘’ The variance increasing.  Thus, heteroskedasticity exist‘’

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Regression 2 Treat Heteroskedasticity Using Logged

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Coefficient Standard Error  t-ratio constant   .6607206 .0922733   7.16  InGovernment .0005441   .0180529 0.03 InInvestment  .2559683 .0187215 13.67 InConsumption .7264814 .0210383 34.53 InImport -.3035008 .0260145 -11.67 InExport .3190214 .01768 18.04

n=185 R-squared= 0.9989 F-statistic= 33578.19 Prob> F = 0.0000

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A 1% increase in  government spending  leads to  a little or no changes  in GDP (coefficient of govt spending) A 1% increase in  Investment  leads to a   increase 25.6%  in GDP (coefficient of investment) A 1% increase in  Consumption  leads to a  72.6% increase  in GDP (coefficient of consumption) A 1% increase in  Import  leads to a  30.4% decrease  in GDP (coefficient of import) A 1% increase in  Export  leads to a  31.9% increase  in GDP (coefficient of export)

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InGov = P>t = 0.976 The P>f result shows the regression is 0.000 which is significant. However, by looking at the InGov, the p>t is greater than 0.05 which is insignificant.

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RSS Sample 1 (Lower Bracket) N= 70 countries        d.o.f= 70-6= 64    By regressing the Logged GDP into to Logged GOV,CONS, INV, IM & EX Logged RSS=0.658722233

RSS Sample 2 (Upper Bracket) N= 70 countries        d.o.f= 70-6= 64     By regressing the Logged GDP into Logged GOV,CONS, INV, IM & EX Logged RSS=  0.098200743

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Logged RSS= 0.658722233      Logged  RSS= 0.098200743 (lower bracket)                                       (upper bracket) ‘’ The variance decreasing.  Thus, the heteroscedasticity is cured‘’

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In summary,  The first regression output shows heteroskedasticity after the GQ test. To fix heteroskedasticity, use logged regression. The second regression improve the variances during GQ test. Hence, the heteroskedasticity is cured.

EXAMINING THE RELATIONSHIP BETWEEN GDP AND NATIONAL INCOME MODEL COMPONENTS OF 185 COUNTRIES IN 2013

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